Supply chain network optimization with environmental impacts

Traditionally the design of supply chains has been based on economic objectives. As societal environment concerns grow, environmental aspects are also emerging, at the industry level, as decisive factors within the context of supply chain management. The investment towards logistics structures that consider both economic and environmental performance is nowadays an important research topic. However, much is still to be done. This paper, addresses the planning and design of supply chain structures for annual profit maximization, while considering environmental aspects. The latter are accounted through the Eco-indicator methodology, which is used to quantify the damage to human health. Profit and environmental impacts are balanced through the use of an optimization approach adapted from symmetric fuzzy linear programming (SFLP), while the supply chain is modelled as a mixed integer linear programming (MILP) optimization problem using the Resource-Task- Network (RTN) methodology. The obtained model is validated through the solution of an example, where its applicability to supply chain problems is demonstrated

Hierarchical decision making patterns for the placement of physical supply chain entities

One of the most important areas of development within the evolution of commerce, is the acknowledgement that businesses can no longer compete as individual entities, but rather must function as part of a supply chain. Within an ever-competitive business environment, the ultimate success of a business can often be tied directly to the overall functionality and efficiency of its supply chain. Research within the area of supply chain management is vast, with prior contributions exploring the function of a supply chain from a plethora of social, economic, and commerce perspectives. Prior research has extended to evaluate multiple industries and geographies, over a number of economic and social issues (e.g. environmental sustainability through transport route modification, poverty reduction through global value chain refinement), along with core management and commerce areas (e.g. marketing initiatives through production cycle analysis, operations management through production capacity). Substantial contributions exist which focus on the role of supply chain management and the value of refining, optimizing and designing a chain to the requirements of an industry, economic environment, or business process. In addition to investigation on the definition, function, and applicability of the concept, prior contributions have effectively demonstrated the value of supply chain management in gaining competitive advantage, and improving the overall performance of a business. The notion that supply chain efficiency defines business advantage, has led to exploration of physical configurations and specifications of supply chains; with the primary undertone often centering around evaluating drivers of supply chain optimization, and therein organizational performance. Within existing research, the process of physical site placement, and managerial decision makers within an organization are identified as being key factors in the optimization of a supply chain. As such, a number of prior studies have investigated the drivers which influence physical location decisions, with the majority of research focusing on the impact of geographical location factors. Other studies have centered on the impact of management structure as a catalyst in refining and optimizing a supply chain. While significant research has focused on both areas individually (Barney, 1991; Chopra & Meindl, 2002; Christopher, 1998), relatively little attention has been placed on evaluating the correlation between these paradigms, and therein exploring the root drivers for management decisions. There appears to be substantial value in directly investigating this relationship, as the analysis of this interaction would provide a comprehensive interpretation of specific factors contributing to physical supply chain development decisions. This research evaluated decision making drivers impacting the placement of physical supply chain entities using augmented qualitative and quantitative primary data. One of the main objectives of this study was to define the accepted sequence of decision making priority with respect to land value determination, transportation and accessibility considerations, and tax incentive structures. Data for the study was collected through electronic surveys and interviews, from supply chain managers working at organizations with a minimum annual revenue of $1,000,000 USD. The proposed relationships were evaluated using rigorous statistical analysis including factor analysis and structural equation modelling. Results indicated the existence of a clear sequence in decision structure, with a measurable pattern of priority placed on specific decision criteria. Aspects of corporate culture within the scope of supply chain decision making were explored with insight into the foundation for physical site evaluation. Empirical data suggested the value of land as having the most substantial influence when making physical location decisions. A number of factors influence how managers determine land value, however the location of a site and its proximity to a firms affiliates (e.g. potential partners, strategic alliances) were identified as having the strongest impact. Other considerations including transportation structures, tax incentives, and the ability of a firm to attract highly productive labor also influenced location decisions, albeit to a lesser degree. While prior research suggests businesses often design supply chains with the intention of attracting inexpensive labor, the results of this study were contradictory. Specifically, this study identified a common hierarchical decision making structure, and finds businesses often place value on highly productive labor (not inexpensive labor) when making supply chain location decisions. Fundamentally, the results presented in this study allows firms to gain insight on how decision makers process and interpret information. Establishing the pattern and sequence of decision making priority in the initial physical site placement stage is critical in ascertaining how supply chain networks develop and grow. From an economic standpoint, findings from this study could be applied to competitor assessment, growth planning, and managerial assessment. Based on the notion that competition takes place through supply chain performance, the practical applications of this study provide a meaningful foundation for optimization and therefore competitive advantage. On a larger scale, this contribution is substantial, as it holds value to both academic and business paradigms in further evaluating the definition and optimization potential of a supply chain, and in providing insight into additional areas of business competitiveness

Optimization models of the supply of power structures’ organizational units with centralized procurement

Management of the state power structures’ organizational units for materiel and technical support requires the use of effective tools for supporting decisions, due to the complexity, interdependence, and dynamism of supply in the market economy. The corporate nature of power structures is of particular interest to centralized procurement management, as it provides significant advantages through coordination, eliminating duplication, and economy of scale. This article presents optimization models of the supply of state power structures’ organizational units with centralized procurement, for different levels of simulated materiel and technical support processes. The models allow us to find the most profitable options for state power structures’ organizational supply units in a centre-oriented logistics system in conditions of the changing needs, volume of allocated funds, and logistics costs that accompany the process of supply, by maximizing the provision level of organizational units with necessary material and technical resources for the entire planning period of supply by minimizing the total logistical costs, taking into account the diverse nature and the different priorities of organizational units and material and technical resources

Research Directions in Information Systems for Humanitarian Logistics

This article systematically reviews the literature on using IT (Information Technology) in humanitarian logistics focusing on disaster relief operations. We first discuss problems in humanitarian relief logistics. We then identify the stage and disaster type for each article as well as the article’s research methodology and research contribution. Finally, we identify potential future research directions

Supply optimization model in the hierarchical geographically distributed organization

The strategic importance of the procurement function in the large organizations management requires using effective tools by the logistics management to justify decisions in the supply process. The architecture features of hierarchical geographically distributed organizations allow the use of a hybrid supply scheme that rationally combines the advantages of centralized and decentralized purchasing and supply management (PSM). The article suggests a supply optimization model in the hierarchical geographically distributed organization (HGDO), reflecting the features of a complex, multifactorial and multi-stage procurement process. The model allows to find the optimal options for purchasing and supplying products for the criterion of minimizing the total logistics costs that characterize this process for the entire period of planning HGDO logistics support, taking into account the values of the various parameters of participants and the logistics functions of the procurement process over each period of time. The model is an effective tool for supporting and coordinating decisions made by logistics managers at different levels of management of HGDO based on numerous options for purchasing and supplying products and their budgeting in conditions of the dynamics and diversity of internal and external factors of influence

Supply Chain Management in the Life Science Sector: Does Trust Play a Role?

Supply chain management has emerged as cross functional, cross company concept to improve coordination of entire value chains through coordinated actions of all companies in the value chain. It has received a major push from the availability of Internet-based information and communication technologies. The conditions in certain sectors are favorable for a realization of chain wide supply chain management. In other sectors, however, conditions are more complex and companies and value chains still struggle to exploit the potentials from supply chain management, in particular when it comes to cross enterprise coordination. This paper takes a complex supply network as example and discusses improvement potentials from supply chain management and developments in their implementation as well as barriers to the realization of chain wide supply chain management.supply chain management, trust, life science sector, Agribusiness, Industrial Organization,

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested